bims-covirf Biomed News
on COVID19 risk factors
Issue of 2020‒11‒22
six papers selected by
Catherine Rycroft
BresMed


  1. PLoS One. 2020 ;15(11): e0241541
    Chidambaram V, Tun NL, Haque WZ, Majella MG, Sivakumar RK, Kumar A, Hsu AT, Ishak IA, Nur AA, Ayeh SK, Salia EL, Zil-E-Ali A, Saeed MA, Sarena APB, Seth B, Ahmadzada M, Haque EF, Neupane P, Wang KH, Pu TM, Ali SMH, Arshad MA, Wang L, Baksh S, Karakousis PC, Galiatsatos P.
      BACKGROUND: Understanding the factors associated with disease severity and mortality in Coronavirus disease (COVID-19) is imperative to effectively triage patients. We performed a systematic review to determine the demographic, clinical, laboratory and radiological factors associated with severity and mortality in COVID-19.METHODS: We searched PubMed, Embase and WHO database for English language articles from inception until May 8, 2020. We included Observational studies with direct comparison of clinical characteristics between a) patients who died and those who survived or b) patients with severe disease and those without severe disease. Data extraction and quality assessment were performed by two authors independently.
    RESULTS: Among 15680 articles from the literature search, 109 articles were included in the analysis. The risk of mortality was higher in patients with increasing age, male gender (RR 1.45, 95%CI 1.23-1.71), dyspnea (RR 2.55, 95%CI 1.88-2.46), diabetes (RR 1.59, 95%CI 1.41-1.78), hypertension (RR 1.90, 95%CI 1.69-2.15). Congestive heart failure (OR 4.76, 95%CI 1.34-16.97), hilar lymphadenopathy (OR 8.34, 95%CI 2.57-27.08), bilateral lung involvement (OR 4.86, 95%CI 3.19-7.39) and reticular pattern (OR 5.54, 95%CI 1.24-24.67) were associated with severe disease. Clinically relevant cut-offs for leukocytosis(>10.0 x109/L), lymphopenia(< 1.1 x109/L), elevated C-reactive protein(>100mg/L), LDH(>250U/L) and D-dimer(>1mg/L) had higher odds of severe disease and greater risk of mortality.
    CONCLUSION: Knowledge of the factors associated of disease severity and mortality identified in our study may assist in clinical decision-making and critical-care resource allocation for patients with COVID-19.
    DOI:  https://doi.org/10.1371/journal.pone.0241541
  2. Aging (Albany NY). 2020 Nov 16. 12
    Meng M, Zhao Q, Kumar R, Bai C, Deng Y, Wan B.
      We examined the effects of coronary heart disease (CHD), hypertension and diabetes on the development of severe COVID-19. We performed a comprehensive, systematic literature search for studies published between December 2019 and July 5, 2020 in five databases. The prevalence of severe COVID-19 in patients with CHD, hypertension and diabetes was evaluated through a meta-analysis. Thirty-five articles with 8,170 patients were included, and all the available studies were case series. The pooled odds ratio for the development of severe COVID-19 was 3.21 for patients with CHD (fixed-effects model, 95% CI: 2.58-3.99), 2.27 for patients with hypertension (random-effects model, 95% CI: 1.79-2.90) and 2.34 for patients with diabetes (random-effects model, 95% CI: 1.79-3.05). The heterogeneity of the studies was moderate for the effect of CHD on COVID-19 severity, but was high for the effects of diabetes and hypertension. Funnel plots and Egger's tests revealed no publication bias in the CHD and hypertension analyses, but suggested publication bias in the diabetes analysis. This bias was corrected using the trim-and-fill method, and was ultimately found to have no effect on the results. Our findings suggest patients with CHD, hypertension and diabetes are at greater risk for developing severe COVID-19 than those without these conditions.
    Keywords:  2019-nCoV; COVID-19; coronary heart disease; diabetes; hypertension; severe pneumonia
    DOI:  https://doi.org/10.18632/aging.103991
  3. medRxiv. 2020 Nov 12. pii: 2020.11.09.20228858. [Epub ahead of print]
    Katzenschlager S, Zimmer AJ, Gottschalk C, Grafeneder J, Seitel A, Maier-Hein L, Benedetti A, Larmann J, Weigand MA, McGrath S, Denkinger CM.
      Background: COVID-19 has been reported in over 40million people globally with variable clinical outcomes. In this systematic review and meta-analysis, we assessed demographic, laboratory and clinical indicators as predictors for severe courses of COVID-19.Methods: We systematically searched multiple databases (PubMed, Web of Science Core Collection, MedRvix and bioRvix) for publications from December 2019 to May 31 st 2020. Random-effects meta-analyses were used to calculate pooled odds ratios and differences of medians between (1) patients admitted to ICU versus non-ICU patients and (2) patients who died versus those who survived. We adapted an existing Cochrane risk-of-bias assessment tool for outcome studies.
    Results: Of 6,702 unique citations, we included 88 articles with 69,762 patients. There was concern for bias across all articles included. Age was strongly associated with mortality with a difference of medians (DoM) of 13.15 years (95% confidence interval (CI) 11.37 to 14.94) between those who died and those who survived. We found a clinically relevant difference between non-survivors and survivors for C-reactive protein (CRP; DoM 69.10, CI 50.43 to 87.77), lactate dehydrogenase (LDH; DoM 189.49, CI 155.00 to 223.98), cardiac troponin I (cTnI; DoM 21.88, CI 9.78 to 33.99) and D-Dimer (DoM 1.29mg/L, CI 0.9 - 1.69). Furthermore, cerebrovascular disease was the co-morbidity most strongly associated with mortality (Odds Ratio 3.45, CI 2.42 to 4.91) and ICU admission (Odds Ratio 5.88, CI 2.35 to 14.73).
    Discussion: This comprehensive meta-analysis found age, cerebrovascular disease, CRP, LDH and cTnI to be the most important risk-factors in predicting severe COVID-19 outcomes and will inform decision analytical tools to support clinical decision-making.
    Summary: In this systematic review we meta-analyzed 88 articles for risk factors of ICU admission and mortality in COVID-19. We found age, cerebrovascular disease, CRP, LDH and cTnI are the most important risk-factors for ICU admission or mortality.
    DOI:  https://doi.org/10.1101/2020.11.09.20228858
  4. Medicine (Baltimore). 2020 Nov 20. 99(47): e23315
    Ji P, Zhu J, Zhong Z, Li H, Pang J, Li B, Zhang J.
      Our study aimed to assess the existing evidence on whether severe coronavirus disease 2019 (COVID-19) is associated with elevated inflammatory markers.The PubMed, Embase, Web of Science, Scopus, Chinese National Knowledge Infrastructure, WanFang, and China Science and Technology Journal databases were searched to identify studies published between January 1 and April 21, 2020 that assayed inflammatory markers in COVID-19 patients. Three reviewers independently examined the literature, extracted relevant data, and assessed the risk of publication bias before including the meta-analysis studies.Fifty-six studies involving 8719 COVID-19 patients were identified. Meta-analysis showed that patients with severe disease showed elevated levels of white blood cell count (WMD: 1.15, 95% CI: 0.78-1.52), C-reactive protein (WMD: 38.85, 95% CI: 31.19-46.52), procalcitonin (WMD: 0.08, 95% CI: 0.06-0.11), erythrocyte sedimentation rate (WMD: 10.15, 95% CI: 5.03-15.46), interleukin-6 (WMD: 23.87, 95% CI: 15.95-31.78), and interleukin-10 (WMD: 2.12, 95% CI: 1.97-2.28). Similarly, COVID-19 patients who died during follow-up showed significantly higher levels of white blood cell count (WMD: 4.11, 95% CI: 3.25-4.97), C-reactive protein (WMD: 74.18, 95% CI: 56.63-91.73), procalcitonin (WMD: 0.26, 95% CI: 0.11-0.42), erythrocyte sedimentation rate (WMD: 10.94, 95% CI: 4.79-17.09), and interleukin-6 (WMD: 59.88, 95% CI: 19.46-100.30) than survivors.Severe COVID-19 is associated with higher levels of inflammatory markers than a mild disease, so tracking these markers may allow early identification or even prediction of disease progression.
    DOI:  https://doi.org/10.1097/MD.0000000000023315
  5. Clin Infect Dis. 2020 Nov 19. pii: ciaa1729. [Epub ahead of print]
    McLaughlin JM, Khan F, Pugh S, Angulo FJ, Schmidt HJ, Isturiz RE, Jodar L, Swerdlow DL.
      BACKGROUND: The United States has been heavily impacted by the COVID-19 pandemic. Understanding micro-level patterns in US rates of COVID-19 can inform specific prevention strategies.METHODS: Using a negative binomial mixed-effects regression model we evaluated the association between a broad set of US county-level sociodemographic, economic, and health-status-related characteristics and cumulative rates of laboratory-confirmed COVID-19 cases and deaths between January 22, 2020 and August 31, 2020.
    RESULTS: Rates of COVID-19 cases and deaths were higher in US counties that were more urban or densely-populated or that had more crowded housing, air pollution, women, 20-49-year-olds, racial/ethnic minorities, residential segregation, income inequality, uninsured, diabetics, or mobility outside the home during the pandemic.
    CONCLUSIONS: To our knowledge, this study provides the most comprehensive multivariable analysis of county-level predictors of rates of COVID-19 cases and deaths conducted to date. Our findings make clear that ensuring that COVID-19 preventive measures, including vaccines when available, reach vulnerable and minority communities and are distributed in a manner that meaningfully disrupts transmission (in addition to protecting those at highest risk of severe disease) will likely be critical to stem the pandemic.
    DOI:  https://doi.org/10.1093/cid/ciaa1729
  6. J Med Virol. 2020 Nov 17.
    Yang J, Tian C, Chen Y, Zhu C, Chi H, Li J.
      AIMS: This review aimed to evaluate the impact of obesity on the onset, exacerbation, and mortality of COVID-19; and compare the effects of different degrees of obesity.MATERIALS AND METHODS: PubMed, EMBASE, and Web of Science were searched to find articles published between December 1, 2019, and July 27, 2020. Only observational studies with specific obesity definition were included. Literature screening and data extraction were conducted simultaneously by two researchers. Random-effects model was used to merge the effect quantity. Sensitivity analysis, subgroup analysis and meta-regression analysis were used to deal with the heterogeneity among studies.
    RESULTS: Forty-one studies with 219543 subjects and 115635 COVID-19 patients were included. Subjects with obesity were more likely to have positive SARS-CoV-2 test results (OR = 1.50, 95% CI: 1.37-1.63, I2 = 69.2%); COVID-19 patients with obesity had a higher incidence of hospitalization (OR = 1.54, 95% CI: 1.33-1.78, I2 = 60.9%); Hospitalized COVID-19 patients with obesity had a higher incidence of ICU admission (OR = 1.48, 95% CI: 1.24-1.77, I2 = 67.5%), invasive mechanical ventilation (OR = 1.47, 95% CI: 1.31-1.65, I2 = 18.8%), and in-hospital mortality (OR = 1.14, 95% CI: 1.04-1.26, I2 = 74.4%). A higher degree of obesity also indicated a higher risk of almost all the above events. Region may be one of the causes of heterogeneity.
    CONCLUSIONS: Obesity could promote the occurrence of the whole course of COVID-19. A higher degree of obesity may predict a higher risk. Further basic and clinical therapeutic researches need to be strengthened. This article is protected by copyright. All rights reserved.
    Keywords:  COVID-19; ICU admission; hospitalization; in-hospital mortality; invasive mechanical ventilation; obesity; positive SARA-CoV-2 test result
    DOI:  https://doi.org/10.1002/jmv.26677